1. Field of the Invention
This invention relates to a method for autonomic data assurance, and particularly to a method for automating an auditing process where modifications to a system are predicted and automatically verified by a pattern recognition mechanism.
2. Description of Background
A common problem in software development is how to verify that a complex software element that provides a data altering function (or service) integrates correctly and produces predictable and valid output. As an example, an e-commerce component is considered that is responsible for processing an order.
The e-commerce component is integrated with several different components. These components include: an order capture component, which is usually a web interface that collects user input about the order, an order processing component, which is a main element that coordinates all other elements, a catalog component, which is utilized to check if entries in the order match with offered items in the store catalog, and if pre-processed prices are correct, an inventory component, a fulfillment component, a shipping component, tax components, a payment component, and an external payment provider component.
This complex function of order processing involves several different database values, calculates new values, and updates the database accordingly at the end of the process. In some specific processes, such as the prior example of the order processing system, these modifications follow an established pattern, which can be predicted and automatically verified for data assurance purposes. For processes involving monetary transactions, assurance is often a required element and is performed manually, e.g., human review of orders and associated payment reports to make sure no discrepancies have occurred. However, this manual assurance by human review is expensive and time consuming.
Considering the limitations of the aforementioned methods, it is clear that there is a need for a method for reducing human intervention when performing an auditing process. In the proposed method an automatic data assurance module compares and then selects patterns that can be automatically audited. In other words, a method of data assurance for e-commerce where modifications to a system are predicted and verified for data assurance by means of pattern recognition is highly desirable.